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Coverage of highly-cited documents in Google Scholar, Web of Science, and Scopus: a multidisciplinary comparison

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Coverage of highly-cited documents in Google Scholar, Web of Science, and Scopus: a multidisciplinary comparison

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dc.contributor.author Martín-Martín, Alberto es_ES
dc.contributor.author Orduña Malea, Enrique es_ES
dc.contributor.author Delgado-López-Cózar, Emilio es_ES
dc.date.accessioned 2020-06-11T03:32:48Z
dc.date.available 2020-06-11T03:32:48Z
dc.date.issued 2018-09 es_ES
dc.identifier.issn 0138-9130 es_ES
dc.identifier.uri http://hdl.handle.net/10251/145981
dc.description.abstract [EN] This study explores the extent to which bibliometric indicators based on counts of highly-cited documents could be affected by the choice of data source. The initial hypothesis is that databases that rely on journal selection criteria for their document coverage may not necessarily provide an accurate representation of highly-cited documents across all subject areas, while inclusive databases, which give each document the chance to stand on its own merits, might be better suited to identify highly-cited documents. To test this hypothesis, an analysis of 2515 highly-cited documents published in 2006 that Google Scholar displays in its Classic Papers product is carried out at the level of broad subject categories, checking whether these documents are also covered in Web of Science and Scopus, and whether the citation counts offered by the different sources are similar. The results show that a large fraction of highly-cited documents in the Social Sciences and Humanities (8.6¿28.2%) are invisible to Web of Science and Scopus. In the Natural, Life, and Health Sciences the proportion of missing highly-cited documents in Web of Science and Scopus is much lower. Furthermore, in all areas, Spearman correlation coefficients of citation counts in Google Scholar, as compared to Web of Science and Scopus citation counts, are remarkably strong (.83¿.99). The main conclusion is that the data about highly-cited documents available in the inclusive database Google Scholar does indeed reveal significant coverage deficiencies in Web of Science and Scopus in several areas of research. Therefore, using these selective databases to compute bibliometric indicators based on counts of highly-cited documents might produce biased assessments in poorly covered areas. es_ES
dc.description.sponsorship Alberto Martín-Martín enjoys a four-year doctoral fellowship (FPU2013/05863) granted by the Ministerio de Educación, Cultura, y Deportes (Spain). es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Scientometrics es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Highly-cited documents es_ES
dc.subject Google Scholar es_ES
dc.subject Web of Science es_ES
dc.subject Scopus es_ES
dc.subject Coverage es_ES
dc.subject Academic journals es_ES
dc.subject Classic papers es_ES
dc.subject.classification BIBLIOTECONOMIA Y DOCUMENTACION es_ES
dc.title Coverage of highly-cited documents in Google Scholar, Web of Science, and Scopus: a multidisciplinary comparison es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s11192-018-2820-9 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MECD//FPU2013%2F05863/ES/FPU2013%2F05863/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicación Audiovisual, Documentación e Historia del Arte - Departament de Comunicació Audiovisual, Documentació i Història de l'Art es_ES
dc.description.bibliographicCitation Martín-Martín, A.; Orduña Malea, E.; Delgado-López-Cózar, E. (2018). Coverage of highly-cited documents in Google Scholar, Web of Science, and Scopus: a multidisciplinary comparison. Scientometrics. 116(3):2175-2188. https://doi.org/10.1007/s11192-018-2820-9 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s11192-018-2820-9 es_ES
dc.description.upvformatpinicio 2175 es_ES
dc.description.upvformatpfin 2188 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 116 es_ES
dc.description.issue 3 es_ES
dc.relation.pasarela S\374448 es_ES
dc.contributor.funder Ministerio de Educación, Cultura y Deporte es_ES
dc.description.references Acharya, A. (2015). What happens when your library is worldwide and all articles are easy to find? Retrieved June 19, 2018, from https://youtu.be/S-f9MjQjLsk?t=7m9s . es_ES
dc.description.references Acharya, A., Verstak, A., Suzuki, H., Henderson, S., Iakhiaev, M., Lin, C. C. Y., & Shetty, N. (2014). Rise of the rest: The growing impact of non-elite journals. Retrieved June 19, 2018, from http://arxiv.org/abs/1410.2217 . es_ES
dc.description.references Archambault, É., Vignola-Gagné, É., Côté, G., Larivière, V., & Gingrasb, Y. (2006). Benchmarking scientific output in the social sciences and humanities: The limits of existing databases. Scientometrics, 68(3), 329–342. https://doi.org/10.1007/s11192-006-0115-z . es_ES
dc.description.references Bar-Ilan, J. (2008). Which h-index?—A comparison of WoS, Scopus and Google Scholar. Scientometrics, 74(2), 257–271. https://doi.org/10.1007/s11192-008-0216-y . es_ES
dc.description.references Bar-Ilan, J. (2010). Citations to the “Introduction to informetrics” indexed by WOS, Scopus and Google Scholar. Scientometrics, 82(3), 495–506. https://doi.org/10.1007/s11192-010-0185-9 . es_ES
dc.description.references Bornmann, L., & Leydesdorff, L. (2018). Count highly-cited papers instead of papers with h citations: Use normalized citation counts and compare “like with like”! Scientometrics, 115(2), 1119–1123. https://doi.org/10.1007/s11192-018-2682-1 . es_ES
dc.description.references Bornmann, L., & Marx, W. (2014). How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations. Scientometrics, 98(1), 487–509. https://doi.org/10.1007/s11192-013-1161-y . es_ES
dc.description.references Bornmann, L., Marx, W., Schier, H., Rahm, E., Thor, A., & Daniel, H.-D. (2009). Convergent validity of bibliometric Google Scholar data in the field of chemistry—Citation counts for papers that were accepted by Angewandte Chemie International Edition or rejected but published elsewhere, using Google Scholar, Science Citation Index, Scopus, and Chemical Abstracts. Journal of Informetrics, 3(1), 27–35. https://doi.org/10.1016/j.joi.2008.11.001 . es_ES
dc.description.references Chavarro, D., Ràfols, I., & Tang, P. (2018). To what extent is inclusion in the Web of Science an indicator of journal ‘quality’? Research Evaluation, 27(2), 106–118. https://doi.org/10.1093/reseval/rvy001 . es_ES
dc.description.references Clarivate Analytics. (2017). Emerging Sources Citation Index Backfile (2005–2014). Retrieved June 19, 2018, from https://clarivate.com/wp-content/uploads/2017/10/M255-Crv_SAR_ESCI-infographic-FA.pdf . es_ES
dc.description.references De Solla Price, D. (1976). A general theory of bibliometric and other cumulative advantage processes. Journal of the American Society for Information Science, 27(5), 292–306. https://doi.org/10.1002/asi.4630270505 . es_ES
dc.description.references de Winter, J. C. F., Zadpoor, A. A., & Dodou, D. (2013). The expansion of Google Scholar versus Web of Science: A longitudinal study. Scientometrics, 98(2), 1547–1565. https://doi.org/10.1007/s11192-013-1089-2 . es_ES
dc.description.references Delgado López-Cózar, E., Martín-Martín, A., & Orduna-Malea, E. (2017). Classic papers: déjà vu, a step further in the bibliometric exploitation of Google Scholar (EC3’s Working Papers No. 24). Retrieved June 19, 2018, from https://arxiv.org/abs/1706.09258 . es_ES
dc.description.references Delgado López-Cózar, E., Orduna-Malea, E., & Martín-Martín, A. (2018). Google Scholar as a data source for research assessment. In W. Glaenzel, H. Moed, U. Schmoch & M. Thelwall (Eds.), Springer handbook of science and technology indicators. Berlin: Springer. es_ES
dc.description.references Delgado López-Cózar, E., Robinson-García, N., & Torres-Salinas, D. (2014). The Google scholar experiment: How to index false papers and manipulate bibliometric indicators. Journal of the Association for Information Science and Technology, 65(3), 446–454. https://doi.org/10.1002/asi.23056 . es_ES
dc.description.references Else, H. (2018). How I scraped data from Google Scholar. Nature. https://doi.org/10.1038/d41586-018-04190-5 . es_ES
dc.description.references Frandsen, T. F., & Nicolaisen, J. (2008). Intradisciplinary differences in database coverage and the consequences for bibliometric research. Journal of the American Society for Information Science and Technology, 59(10), 1570–1581. https://doi.org/10.1002/asi.20817 . es_ES
dc.description.references García-Pérez, M. A. (2010). Accuracy and completeness of publication and citation records in the Web of Science, PsycINFO, and Google Scholar: A case study for the computation of h indices in Psychology. Journal of the American Society for Information Science and Technology, 61(10), 2070–2085. https://doi.org/10.1002/asi.21372 . es_ES
dc.description.references Halevi, G., Moed, H., & Bar-Ilan, J. (2017). Suitability of Google Scholar as a source of scientific information and as a source of data for scientific evaluation—Review of the Literature. Journal of Informetrics, 11(3), 823–834. https://doi.org/10.1016/J.JOI.2017.06.005 . es_ES
dc.description.references Harzing, A.-W. (2013). A preliminary test of Google Scholar as a source for citation data: A longitudinal study of Nobel prize winners. Scientometrics, 94(3), 1057–1075. https://doi.org/10.1007/s11192-012-0777-7 . es_ES
dc.description.references Harzing, A.-W. (2016). Sacrifice a little accuracy for a lot more comprehensive coverage. Retrieved June 19, 2018, from https://harzing.com/blog/2016/08/sacrifice-a-little-accuracy-for-a-lot-more-comprehensive-coverage . es_ES
dc.description.references Hicks, D., Wouters, P., Waltman, L., de Rijcke, S., & Rafols, I. (2015). Bibliometrics: The Leiden Manifesto for research metrics. Nature, 520(7548), 429–431. https://doi.org/10.1038/520429a . es_ES
dc.description.references Kousha, K., & Thelwall, M. (2008). Sources of Google Scholar citations outside the Science Citation Index: A comparison between four science disciplines. Scientometrics, 74(2), 273–294. https://doi.org/10.1007/s11192-008-0217-x . es_ES
dc.description.references Levine-Clark, M., & Gil, E. L. (2008). A comparative citation analysis of Web of Science, Scopus, and Google Scholar. Journal of Business & Finance Librarianship, 14(1), 32–46. https://doi.org/10.1080/08963560802176348 . es_ES
dc.description.references Leydesdorff, L., Bornmann, L., Mutz, R., & Opthof, T. (2011). Turning the tables on citation analysis one more time: Principles for comparing sets of documents. Journal of the American Society for Information Science and Technology, 62(7), 1370–1381. https://doi.org/10.1002/asi.21534 . es_ES
dc.description.references Martín-Martín, A., Costas, R., van Leeuwen, T., & Delgado López-Cózar, E. (2018). Evidence of Open Access of scientific publications in Google Scholar: A large-scale analysis. https://doi.org/10.17605/osf.io/k54uv . es_ES
dc.description.references Martín-Martín, A., Orduna-Malea, E., Ayllón, J. M., & Delgado López-Cózar, E. (2016). A two-sided academic landscape: snapshot of highly-cited documents in Google Scholar (1950–2013). Revista Española de Documentacion Cientifica, 39(4), e149. https://doi.org/10.3989/redc.2016.4.1405 . es_ES
dc.description.references Martín-Martín, A., Orduña-Malea, E., Ayllón, J. M., & Delgado-López-Cózar, E. (2014). Does Google Scholar contain all highly cited documents (1950–2013)? (EC3 Working Papers No. 19). Retrieved June 19, 2018, from http://arxiv.org/abs/1410.8464 . es_ES
dc.description.references Martín-Martín, A., Orduna-Malea, E., & Delgado López-Cózar, E. (2018). Data and code for: Coverage of highly-cited documents in Google Scholar, Web of Science, and Scopus: A multidisciplinary comparison. https://doi.org/10.17605/OSF.IO/DNQZK . es_ES
dc.description.references Martin-Martin, A., Orduna-Malea, E., Harzing, A.-W., & Delgado López-Cózar, E. (2017). Can we use Google Scholar to identify highly-cited documents? Journal of Informetrics, 11(1), 152–163. https://doi.org/10.1016/j.joi.2016.11.008 . es_ES
dc.description.references Meho, L. I., & Yang, K. (2007). Impact of data sources on citation counts and rankings of LIS faculty: Web of Science versus Scopus and Google Scholar. Journal of the American Society for Information Science and Technology, 58(13), 2105–2125. https://doi.org/10.1002/asi.20677 . es_ES
dc.description.references Mingers, J., & Lipitakis, E. A. E. C. G. (2010). Counting the citations: A comparison of Web of Science and Google Scholar in the field of business and management. Scientometrics, 85(2), 613–625. https://doi.org/10.1007/s11192-010-0270-0 . es_ES
dc.description.references Moed, H. F., Bar-Ilan, J., & Halevi, G. (2016). A new methodology for comparing Google Scholar and Scopus. Journal of Informetrics, 10(2), 533–551. https://doi.org/10.1016/j.joi.2016.04.017 . es_ES
dc.description.references Mongeon, P., & Paul-Hus, A. (2016). The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics, 106(1), 213–228. https://doi.org/10.1007/s11192-015-1765-5 . es_ES
dc.description.references Orduna-Malea, E., Ayllón, J. M., Martín-Martín, A., & Delgado López-Cózar, E. (2015). Methods for estimating the size of Google Scholar. Scientometrics, 104(3), 931–949. https://doi.org/10.1007/s11192-015-1614-6 . es_ES
dc.description.references Orduña-Malea, E., Martín-Martín, A., Ayllón, J. M., & Delgado López-Cózar, E. (2016). La revolución Google Scholar: Destapando la caja de Pandora académica. Granada: Universidad de Granada. es_ES
dc.description.references Orduna-Malea, E., Martín-Martín, A., & Delgado López-Cózar, E. (2017). Google Scholar as a source for scholarly evaluation: A bibliographic review of database errors. Revista Española de Documentación Científica, 40(4), e185. https://doi.org/10.3989/redc.2017.4.1500 . es_ES
dc.description.references Rahimi, S., & Chandrakumar, V. (2014). A comparison of citation coverage of traditional and web citation databases in medical science. Malaysian Journal of Library and Information Science, 19(3), 1–11. Retrieved June 19, 2018, from http://jice.um.edu.my/index.php/MJLIS/article/view/1779 . es_ES
dc.description.references Sud, P., & Thelwall, M. (2014). Evaluating altmetrics. Scientometrics, 98(2), 1131–1143. https://doi.org/10.1007/s11192-013-1117-2 . es_ES
dc.description.references Thelwall, M. (2017). Three practical field normalised alternative indicator formulae for research evaluation. Journal of Informetrics, 11(1), 128–151. https://doi.org/10.1016/j.joi.2016.12.002 . es_ES
dc.description.references Thelwall, M., & Fairclough, R. (2017). The accuracy of confidence intervals for field normalised indicators. Journal of Informetrics, 11(2), 530–540. https://doi.org/10.1016/j.joi.2017.03.004 . es_ES
dc.description.references van Leeuwen, T. N., Moed, H. F., Tijssen, R. J. W., Visser, M. S., & Van Raan, A. F. J. (2001). Language biases in the coverage of the Science Citation Index and its consequences for international comparisons of national research performance. Scientometrics, 51(1), 335–346. https://doi.org/10.1023/A:1010549719484 . es_ES
dc.description.references Vine, R. (2006). Google Scholar. Journal of the Medical Library Association, 94(1), 97. Retrieved from https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1324783/ . es_ES


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